Finding Gene Regulatory Networks in Psoriasis: Application of a Tree-Based Machine Learning Approach

Frontiers in Immunology

José A. M. Borghans¹  Carlotta Schieler¹  Aridaman Pandit¹  Jingwen Deng²  Chuanjian Lu² 

[1] Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands;The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China;

关键词: psoriasis;    gene regulatory network;    machine learning;    transcriptome;    regulators;   

DOI  :  10.3389/fimmu.2022.921408

来源: DOAJ

【 摘 要 】

Psoriasis is a chronic inflammatory skin disorder. Although it has been studied extensively, the molecular mechanisms driving the disease remain unclear. In this study, we utilized a tree-based machine learning approach to explore the gene regulatory networks underlying psoriasis. We then validated the regulators and their networks in an independent cohort. We identified some key regulators of psoriasis, which are candidates to serve as potential drug targets and disease severity biomarkers. According to the gene regulatory network that we identified, we suggest that interferon signaling represents a key pathway of psoriatic inflammation.

【 授权许可】

Unknown